Public supporting artefacts for the NextLeap graduation case study (“Increase wishlist→purchase conversion within 30 days — no monetary incentives”). The AI Discovery Engine is a separate deployed app.
AI Discovery Engine
19,143 public conversations → 12 induced frictions, quantified & ranked.
Metric decomposition — where wishlist→purchase breaks
Business metric → product outcomes → behaviour funnel (Part 2).
Interview instruments (n=6, four behavioural groups)
Screener, recent-episode guide, usability tasks, exit survey, synthesis template (Part 3).
Problem definition
Segment, outcome, root cause, workarounds, user & business value (Part 4).
Success metrics & risks
Leading indicators, guardrails, definitions, rationale; risks & mitigations (Parts 6–7).
Case-study submission for a PM fellowship. All catalog data in this prototype is simulated; review texts are patterned on real public complaints surfaced by the discovery engine. Not affiliated with Myntra.